This application relates generally to biometrics. More specifically, this application relates to fingerprint spoof detection.
“Biometrics” refers generally to the statistical analysis of characteristics of living bodies. One category of biometrics includes “biometric identification,” which commonly operates under one of two modes to provide automatic identification of people or to verify purported identities of people. Biometric sensing technologies measure the physical features or behavioral characteristics of a person and compare those features to similar prerecorded measurements to determine whether there is a match. Physical features that are commonly used for biometric identification includes faces, irises, hand geometry, vein structure, and fingerprints. The last of these is the most prevalent of all biometric-identification features. Currently, methods for analyzing collected fingerprints include optical, capacitive, radio-frequency, thermal, ultrasonic, and several other less common techniques.
Biometric sensors, particularly fingerprint biometric sensors, are generally prone to being defeated by various forms of spoof samples. In the case of fingerprint readers, a variety of methods are known in the art for presenting readers with a fingerprint pattern of an authorized user that is embedded in some kind of inanimate material such as paper, gelatin, epoxy, latex, and the like. Thus, even if a fingerprint reader can be considered to reliably determine the presence or absence of a matching fingerprint pattern, it is also critical to the overall system security to ensure that the matching pattern is being acquired from a genuine, living finger, which may be difficult to ascertain with many common sensors.
There is accordingly a general need in the art for methods and systems that permit discrimination between legitimate and spoof presentations of fingerprints.